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H.E. Stephanou, S.Y. Lu, "Measuring Consensus Effectiveness by a Generalized Entropy Criterion," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 4, pp. 544554, July, 1988.  
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@article{ 10.1109/34.3916, author = {H.E. Stephanou and S.Y. Lu}, title = {Measuring Consensus Effectiveness by a Generalized Entropy Criterion}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {10}, number = {4}, issn = {01628828}, year = {1988}, pages = {544554}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.3916}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Measuring Consensus Effectiveness by a Generalized Entropy Criterion IS  4 SN  01628828 SP544 EP554 EPD  544554 A1  H.E. Stephanou, A1  S.Y. Lu, PY  1988 KW  set theory; knowledge engineering; artificial intelligence; consensus effectiveness; entropy; knowledge sources; DempsterShafer theory; concept; uncertainty; information theory; knowledge engineering; set theory VL  10 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
A quantitative criterion for measuring the effectiveness of the consensus obtained by pooling evidence from two knowledge sources is introduced. A brief review of the DempsterShafer theory of mathematical evidence, which is based on a settheoretic description of subjective uncertainty, is given. The concept of generalized entropy as a measure of the uncertainty in a knowledge source is also introduced. It is proven that the pooling of evidence by Dempster's rule of combination decreases the total amount of generalized entropy in the knowledge sources. The decrease of entropy corresponds to the focusing of knowledge, and is used as a measure of consensus effectiveness. Several examples are used to illustrate this measure.
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